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Res."],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>\n                      This study aimed to identify the potential inflammatory molecular biomarkers that could be utilized for the early prediction of different subtypes of\n                      <jats:italic>tuberculosis<\/jats:italic>\n                      (TB) in adults.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Plasma samples were obtained from a cohort of adults diagnosed with 48 cases of active TB, including drug-susceptible TB (S-TB, n\u2009=\u200928), multidrug-resistant TB (R-TB, n\u2009=\u200920), latent TB infection (LTBI, n\u2009=\u200920), as well as a control group of healthy individuals without any infection (HC, n\u2009=\u200920). The expression level of 92 inflammatory-related proteins was detecte\n                      <jats:underline>d by<\/jats:underline>\n                      using the high-throughput Olink proteomics platform.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      There were 47 inflammatory proteins showing a significant difference (p\u2009&lt;\u20090.05) among TB, LTBI, and HC groups, and 7 of them differed significantly between HC and LTBI groups, 43 proteins differed considerably between LTBI and TB groups, and overall, CXCL10 and TGF-alpha proteins differed substantially among the three groups which could be used as potential diagnostic biomarkers. Furthermore, SCF demonstrates remarkable discriminatory power in distinguishing TB from LTBI, with an area under the curve (AUC) score of 0.920. SLAMF1 has emerged as the top predictor for distinguishing Sputum Culture-Negative from positive\n                      <jats:italic>tuberculosis<\/jats:italic>\n                      cases, with an AUC of 0.779. The Correlation analyses showed various relationships among co-differentiated proteins. In LTBI versus HC, TGF-alpha and CXCL10 had a strong positive correlation. In non-severe versus severe TB, CXCL10 and CXCL9, as well as TNF and CCL3, were strongly positively correlated, while IL-6 and SCF had a negative correlation. These co-differentiated proteins were found to be enriched in various biological processes and molecular functions related to immune regulation and signaling pathways, such as the p53 signaling pathway, the TNF signaling pathway, and the NF-kappa B signaling pathway, highlighting the complex interplay of these proteins in the immune response to TB infection.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      Inflammation-related proteins exhibited distinct expression profiles in various conditions of TB. These proteins are intercorrelated and involve the pathogenesis of tuberculosis by activating diverse immune cells and promoting the secretion of pro-inflammatory cytokines. Their functions influence cellular phenotypes, which play a crucial regulatory role in the interaction between the host and\n                      <jats:italic>Mycobacterium tuberculosis<\/jats:italic>\n                      . These findings suggest that these proteins are potential disease prevention and treatment targets.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00011-025-02020-9","type":"journal-article","created":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T08:26:43Z","timestamp":1743668803000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Identification of inflammatory protein biomarkers for predicting the different subtype of adult with tuberculosis: an Olink proteomic study"],"prefix":"10.1007","volume":"74","author":[{"given":"Yunlin","family":"Song","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Buzukela","family":"Abuduaini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinting","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiyuan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guirong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaobo","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,4,1]]},"reference":[{"issue":"6","key":"2020_CR1","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1016\/S2213-2600(22)00092-3","volume":"10","author":"K Dheda","year":"2022","unstructured":"Dheda K, et al. 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